An AI-based computer system can gather data and use that data to make decisions or solve problems – using algorithms to perform tasks that, if done by a human, would be said to require intelligence. The benefits created by AI and machine learning (ML) systems for better health care, safer transportation, and greater efficiencies across the globe are already happening. But the increased amounts of data and computing power that enable sophisticated AI and ML models raise questions about the privacy impacts, ethical consequences, fairness, and real world harms if the systems are not designed and managed responsibly. FPF works with commercial, academic, and civil society supporters and partners to develop best practices for managing risk in AI and ML and assess whether historical data protection practices such as fairness, accountability, and transparency are sufficient to answer the ethical questions they raise.
FPF Releases Generative AI Internal Policy Checklist To Guide Development of Policies to Promote Responsible Employee Use of Generative AI Tools
Today, the Future of Privacy Forum (FPF) releases the Generative AI for Organizational Use: Internal Policy Checklist. With the proliferation of employee use of generative AI tools, this checklist provides organizations with a powerful tool to help revise their internal policies and procedures to ensure that employees are using generative AI in a way that […]